EarthServer provides access to Open Climate and Air Quality Data for #OpenDataHack at ECMWF

jwagemann Mon, 13/03/2017 - 15:00
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Over 70 developers, data wranglers, scientists and data enthusiasts came to #OpenDataHack @ECMWF on 4 and 5 March 2017 to explore creative uses of open weather and climate data from ECMWF and the three Copernicus services: the Climate Change Service (C3S), the Atmospheric Monitoring Service (CAMS) and the Emergency Management Service (EMS).

The aim was to raise awareness of freely available data from ECMWF and Copernicus and to have direct contact with users who are interested to work with ECMWF open data. A data service catalogue gave an overview of multiple data services offered by ECMWF, including two OGC-based web services: (1) Web Mapping Service and (2) Web Coverage Service, which is currently setup at ECMWF and acts as climate science data provider of EarthServer-2.

ECMWF’s Web Coverage Service is an explorative service and offers a full range of complex meteorological and climate data, from 3D climate reanalysis data up to 5D river discharge forecast data of the Global Flood Awareness System project. Just in time for the hackathon, newly available Copernicus datasets for air quality and fire hazard have been made available via the WCS service: high-resolution data on ozone, particulate matter 2.5 and 10 and nitrogen dioxide concentration for Europe from CAMS and fire weather index forecast data from CEMS.

The hackathon was divided into three challenge categories: (1) Get Out, (2) Get Geeky and (3) Get Creative, and a judging panel of six, including Florence Rabier, Director General of ECMWF and Denise McKenzie, Executive Director for Communications and Outreach of the Open Geospatial Consortium nominated a winner for each category.

The winner of the Get Out challenge was the project HydroNEXT, who developed a web application that uses river discharge forecast data from ECMWF’s Web Coverage Service and river flow data from the Copernicus SWICCA project to calculate projected energy generation of a specific hydro-electrical plant. The project integrated on-demand data access via a WCS into their geospatial workflow.

Example from the winning team HydroNext how an OGC-based Web Coverage Service can be part of the data processing workflow (Photo: Stephan Siemen)

The winner of the Get Geeky challenge was the project "Reading Buses accident and breakdown prediction", who developed a machine-learning model that predicts the probability of accidents for buses in response to weather conditions. Besides bus data, the model uses climate reanalysis data, as total precipitation, snow fall, evaporation and total column ozone.

The Get Creative category had two winners: Team Diversity investigated the impact of weather and climate on animal migration in Kenya, based on a geospatial analysis. The second first place was awarded to team CWS+, which developed a water disease prevention system for Kenya. Based on rainfall predictions the system predicts the likelihood of diseases, droughts, water shortage problems and floods.

The hackathon had two main outcomes:

Meteorological data is challenging to access and to work with, especially for users outside the MetOcean community. Most challenging are meteorological data models that can have up to five dimensions and the GRIB data format that is often used in the meteorological domain.

Open weather and climate data is only beneficial when combined with other open data sources. Reading Buses and Snowflake software were two additional open data providers for the #OpenDataHack.

ECMWF’s participation in EarthServer-2 addresses specifically the first challenge by offering a facilitated and on-demand access to ECMWF’s data with the help of a Web Coverage Service. Data users do not have to deal with community-specific data formats anymore, but have direct access to the real data values.

More information on the climate science data provider can be found here.

What if geodata were available for download on the web – what would the next step be, what do users need then? The answer is: ad-hoc analysis using any terminal device, utilising the geodata provider’s server capacity.
This is the objective of the Earthserver project, which relies solely on open standards in order to provide scalable services for multi - dimensional data of all Earth sciences field.